Abstract: This disclosure relates to systems and methods for vehicle guidance. Stereo images may be obtained at different times using a stereo image sensor. A depth image may be determined based on an earlier obtained pair of stereo images. The depth image may be refined based on predictions of an earlier stereo image and a later obtained stereo image. Depth information for an environment around a vehicle may be obtained. The depth information may characterize distances between the vehicle and the environment around the vehicle. A spherical depth map may be generated from the depth information. Maneuver controls for the vehicle may be provided based on the spherical depth map.

Abstract: This disclosure relates to systems and methods for controlling an unmanned aerial vehicle. Boundaries of a user-defined space may be obtained. The boundaries of the user-defined space may be fixed with respect to some reference frame. A user-defined operation associated with the user-selected space may be obtained. Position of the unmanned aerial vehicle may be tracked during an unmanned aerial flight. Responsive to the unmanned aerial vehicle entering the user-defined space, the unmanned aerial vehicle may be automatically controlled to perform the user-defined operation.

Abstract: Controlling an unmanned aerial vehicle may include obtaining a first image from a fixed orientation image capture device of the unmanned aerial vehicle, obtaining a second image from an adjustable orientation image capture device of the unmanned aerial vehicle, obtaining feature correlation data based on the first image and the second image, obtaining relative image capture device orientation calibration data based on the feature correlation data, the relative image capture device orientation calibration data indicating an orientation of the adjustable orientation image capture device relative to the fixed orientation image capture device, obtaining relative object orientation data based on the relative image capture device orientation calibration data, the relative object orientation data representing a three-dimensional orientation of an external object relative to the adjustable orientation image capture device, and controlling a trajectory of the unmanned aerial vehicle in response to the relative object

Abstract: A GNSS antenna system for receiving GNSS signals in the L1 and L2/L5 frequency band, and to an unmanned aerial vehicle (UAV) comprising the GNSS antenna system.

Abstract: The invention relates to an unmanned aerial vehicle (UAV), the operation of a UAV, and the control of a UAV. Aspects of the invention relate to a UAV including a directional distance measuring module for inspecting/surveying/measuring/digitizing the UAV's environment.

Abstract: Controlling an unmanned aerial vehicle to traverse a portion of an operational environment of the unmanned aerial vehicle may include obtaining an object detection type, obtaining object detection input data, obtaining relative object orientation data based on the object detection type and the object detection input data, and performing an object avoidance operation based on the relative object orientation data. The object detection type may be monocular object detection, which may include obtaining the relative object orientation data by obtaining motion data indicating a change of spatial location for the unmanned aerial vehicle between obtaining the first image and obtaining the second image based on searching along epipolar lines to obtain optical flow data.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include, receiving an image from an image sensor; storing a sequence of images captured after the image in a buffer; determining an orientation error between the orientation of the image sensor and an orientation setpoint during capture of the image; determining a rotation corresponding to the orientation error based on orientation estimates from the sequence of orientation estimates corresponding to the sequence of images; and invoking an electronic image stabilization module to correct the image to obtain a stabilized image, in which the electronic image stabilization module corrects the image for the rotation corresponding to the orientation error.

Abstract: The invention relates to an unmanned aerial vehicle (UAV), the operation of a UAV, and the control of a UAV. Aspects of the invention relate to a UAV including a directional distance measuring module for inspecting/surveying/measuring/digitizing the UAV's environment.

Abstract: A vehicle includes systems and methods to guide the vehicle. A sensor detects objects around the vehicle and processor includes a predicted motion component and a predicted imaging component to avoid objects around the vehicle. The system and method then avoid the object if the processor determines that an intersection will occur between the object and the vehicle.

Abstract: This disclosure relates to systems and methods for controlling an unmanned aerial vehicle. Boundaries of a user-defined space may be obtained. The boundaries of the user-defined space may be fixed with respect to some reference frame. A user-defined operation associated with the user-selected space may be obtained. Position of the unmanned aerial vehicle may be tracked during an unmanned aerial flight. Responsive to the unmanned aerial vehicle entering the user-defined space, the unmanned aerial vehicle may be automatically controlled to perform the user-defined operation.

Abstract: Controlling an unmanned aerial vehicle may include obtaining a first image from a fixed orientation image capture device of the unmanned aerial vehicle, obtaining a second image from an adjustable orientation image capture device of the unmanned aerial vehicle, obtaining feature correlation data based on the first image and the second image, obtaining relative image capture device orientation calibration data based on the feature correlation data, the relative image capture device orientation calibration data indicating an orientation of the adjustable orientation image capture device relative to the fixed orientation image capture device, obtaining relative object orientation data based on the relative image capture device orientation calibration data, the relative object orientation data representing a three-dimensional orientation of an external object relative to the adjustable orientation image capture device, and controlling a trajectory of the unmanned aerial vehicle in response to the relative object

Abstract: Controlling an unmanned aerial vehicle may include obtaining a first image from a fixed orientation image capture device of the unmanned aerial vehicle, obtaining a second image from an adjustable orientation image capture device of the unmanned aerial vehicle, obtaining feature correlation data based on the first image and the second image, obtaining relative image capture device orientation calibration data based on the feature correlation data, the relative image capture device orientation calibration data indicating an orientation of the adjustable orientation image capture device relative to the fixed orientation image capture device, obtaining relative object orientation data based on the relative image capture device orientation calibration data, the relative object orientation data representing a three-dimensional orientation of an external object relative to the adjustable orientation image capture device, and controlling a trajectory of the unmanned aerial vehicle in response to the relative object

Abstract: In one aspect of the present disclosure, a module is disclosed for use with a digital image capturing device (DICD) including an integrated sensor-lens assembly (ISLA). The module includes a cradle configured for connection to a housing of the DICD, and at least one dampener that is configured for positioning between the module and the housing of the DICD to reduce vibrations transmitted to the ISLA.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include, based on a sequence of orientation estimates for an image sensor and an orientation setpoint, invoking a mechanical stabilization system to adjust an orientation of the image sensor toward the orientation setpoint; receiving an image from the image sensor; determining an orientation error between the orientation of the image sensor and the orientation setpoint during capture of the image; and, based on the orientation error, invoking an electronic image stabilization module to correct the image for a rotation corresponding to the orientation error to obtain a stabilized image.

Abstract: Controlling an unmanned aerial vehicle may include obtaining a first image from a fixed orientation image capture device of the unmanned aerial vehicle, obtaining a second image from an adjustable orientation image capture device of the unmanned aerial vehicle, obtaining feature correlation data based on the first image and the second image, obtaining relative image capture device orientation calibration data based on the feature correlation data, the relative image capture device orientation calibration data indicating an orientation of the adjustable orientation image capture device relative to the fixed orientation image capture device, obtaining relative object orientation data based on the relative image capture device orientation calibration data, the relative object orientation data representing a three-dimensional orientation of an external object relative to the adjustable orientation image capture device, and controlling a trajectory of the unmanned aerial vehicle in response to the relative object

Abstract: Controlling an unmanned aerial vehicle to traverse a portion of an operational environment of the unmanned aerial vehicle may include obtaining an object detection type, obtaining object detection input data, obtaining relative object orientation data based on the object detection type and the object detection input data, and performing an object avoidance operation based on the relative object orientation data. The object detection type may be monocular object detection, which may include obtaining the relative object orientation data by obtaining motion data indicating a change of spatial location for the unmanned aerial vehicle between obtaining the first image and obtaining the second image based on searching along epipolar lines to obtain optical flow data.

Abstract: A construction machine comprising a chassis, a steering, and a powertrain for driving the construction machine by the chassis, an earth-moving tool for working a terrain, and a measuring system having a first measuring unit configured for generating first measuring data in a first detection range and comprising at least a first camera and a first LiDAR scanner configured for rotating a first measuring beam around a first axis and around a second axis non-parallel to the first axis with a rotating speed of at least 0.5 Hz with respect to each axis, an interface connecting the first measuring unit to a computer configured for, based on the first measuring data, at least one of generating a three-dimensional model of the terrain within the first detection range, identifying an obstacle or a person within the first detection range, and controlling the steering, the powertrain, and/or the earth-moving tool.

Abstract: A robot drive module for driving a rotary joint movement of a robot with at least a rotary drive and at least a rotary encoder arrangement and a method for a robot having such a robot drive module.

Abstract: The disclosure describes systems and methods for a stabilization mechanism. The stabilization mechanism may be used in conjunction with an imaging device. The method may be performed by a control system of the stabilization mechanism and includes obtaining a device setting from an imaging device. The method may also include obtaining a configuration of the stabilization mechanism. The method includes determining a soft stop based on the device setting, the configuration, or both. The soft stop may be a virtual hard stop that indicates to the stabilization mechanism to reduce speed as a field of view of the imaging device approaches the soft stop. The method may also include setting an image stabilization mechanism parameter based on the determined soft stop.

Abstract: This disclosure relates to systems and methods for controlling an unmanned aerial vehicle. Boundaries of a user-defined space may be obtained. The boundaries of the user-defined space may be fixed with respect to some reference frame. A user-defined operation associated with the user-selected space may be obtained. Position of the unmanned aerial vehicle may be tracked during an unmanned aerial flight. Responsive to the unmanned aerial vehicle entering the user-defined space, the unmanned aerial vehicle may be automatically controlled to perform the user-defined operation.